8 papers
Muse Spark Safety & Preparedness Report
Cristina Menghini, Peter Ney, Hamza Kwisaba +117
Muse Spark is the latest large language model developed by Meta. In this report, we first present evaluations for catastrophic risk domains under Meta's Advanced AI Scaling Framewo…
Code World Model Preparedness Report
Daniel Song, Peter Ney, Cristina Menghini +21
This report documents the preparedness assessment of Code World Model (CWM), a model for code generation and reasoning about code from Meta. We conducted pre-release testing across…
LLM Novice Uplift on Dual-Use, In Silico Biology Tasks
Chen Bo Calvin Zhang, Christina Q. Knight, Nicholas Kruus +16
Large language models (LLMs) perform increasingly well on biology benchmarks, but it remains unclear whether they uplift novice users -- i.e., enable humans to perform better than…
Humanity's Last Exam
Long Phan, Alice Gatti, Ziwen Han +1144
Benchmarks are important tools for tracking the rapid advancements in large language model (LLM) capabilities. However, benchmarks are not keeping pace in difficulty: LLMs now achi…
Best Practices for Biorisk Evaluations on Open-Weight Bio-Foundation Models
Boyi Wei, Zora Che, Nathaniel Li +10
Open-weight bio-foundation models present a dual-use dilemma. While holding great promise for accelerating scientific research and drug development, they could also enable bad acto…
Just Read the Question: Enabling Generalization to New Assessment Items with Text Awareness
Arisha Khan, Nathaniel Li, Tori Shen +1
Machine learning has been proposed as a way to improve educational assessment by making fine-grained predictions about student performance and learning relationships between items.…